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Semantic Segmentation

Papers

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Showing 10701–10750 of 14763 papers

TitleStatusHype
SAMST: A Transformer framework based on SAM pseudo label filtering for remote sensing semi-supervised semantic segmentation—0
SAMVG: A Multi-stage Image Vectorization Model with the Segment-Anything Model—0
SANeRF-HQ: Segment Anything for NeRF in High Quality—0
Scale-aware Neural Network for Semantic Segmentation of Multi-resolution Remote Sensing Images—0
SA-NET.v2: Real-time vehicle detection from oblique UAV images with use of uncertainty estimation in deep meta-learning—0
SAN: Scale-Aware Network for Semantic Segmentation of High-Resolution Aerial Images—0
SAQ-SAM: Semantically-Aligned Quantization for Segment Anything Model—0
SAR image segmentation algorithms based on I-divergence-TV model—0
SAR Object Detection with Self-Supervised Pretraining and Curriculum-Aware Sampling—0
SASO: Joint 3D Semantic-Instance Segmentation via Multi-scale Semantic Association and Salient Point Clustering Optimization—0
Satellite Imagery Feature Detection using Deep Convolutional Neural Network: A Kaggle Competition—0
Satellite Sunroof: High-res Digital Surface Models and Roof Segmentation for Global Solar Mapping—0
SATR: Zero-Shot Semantic Segmentation of 3D Shapes—0
SAT: Size-Aware Transformer for 3D Point Cloud Semantic Segmentation—0
SatSynth: Augmenting Image-Mask Pairs through Diffusion Models for Aerial Semantic Segmentation—0
SBSS: Stacking-Based Semantic Segmentation Framework for Very High Resolution Remote Sensing Image—0
Scalable and Equivariant Spherical CNNs by Discrete-Continuous (DISCO) Convolutions—0
Scalable Deep Convolutional Neural Networks for Sparse, Locally Dense Liquid Argon Time Projection Chamber Data—0
Scalable Neural Architecture Search for 3D Medical Image Segmentation—0
Scalable, Proposal-free Instance Segmentation Network for 3D Pixel Clustering and Particle Trajectory Reconstruction in Liquid Argon Time Projection Chambers—0
Scalable Self-Supervised Representation Learning from Spatiotemporal Motion Trajectories for Multimodal Computer Vision—0
Scalable Semantic 3D Mapping of Coral Reefs with Deep Learning—0
Scalable Uncertainty for Computer Vision with Functional Variational Inference—0
Scalable Variational Inference in Log-supermodular Models—0
Scalable Video Object Segmentation with Simplified Framework—0
Scale-aware multi-level guidance for interactive instance segmentation—0
Scale-aware Super-resolution Network with Dual Affinity Learning for Lesion Segmentation from Medical Images—0
Scale Disparity of Instances in Interactive Point Cloud Segmentation—0
Scale Equivariant Neural Networks with Morphological Scale-Spaces—0
Scale Equivariant U-Net—0
Scale-Equivariant UNet for Histopathology Image Segmentation—0
Scale-free and Task-agnostic Attack: Generating Photo-realistic Adversarial Patterns with Patch Quilting Generator—0
Scale Invariant Semantic Segmentation with RGB-D Fusion—0
ScaleNAS: One-Shot Learning of Scale-Aware Representations for Visual Recognition—0
Scale-specific auxiliary multi-task contrastive learning for deep liver vessel segmentation—0
Scale-wise Bidirectional Alignment Network for Referring Remote Sensing Image Segmentation—0
Scaling Vision-based End-to-End Driving with Multi-View Attention Learning—0
Scaling up Image Segmentation across Data and Tasks—0
Scaling up instance annotation via label propagation—0
Scaling Up Quantization-Aware Neural Architecture Search for Efficient Deep Learning on the Edge—0
Scaling Vision Mamba Across Resolutions via Fractal Traversal—0
Scaling White-Box Transformers for Vision—0
Scaling Wide Residual Networks for Panoptic Segmentation—0
SCALPEL: Segmentation Cascades with Localized Priors and Efficient Learning—0
ScanComplete: Large-Scale Scene Completion and Semantic Segmentation for 3D Scans—0
Scan, Materialize, Simulate: A Generalizable Framework for Physically Grounded Robot Planning—0
SCASeg: Strip Cross-Attention for Efficient Semantic Segmentation—0
Scattering Vision Transformer: Spectral Mixing Matters—0
SceneAdapt: Scene-based domain adaptation for semantic segmentation using adversarial learning—0
SceneCut: Joint Geometric and Object Segmentation for Indoor Scenes—0
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All datasetsADE20KNYU-Depth V2Cityscapes testCityscapes valADE20K valPASCAL ContextS3DIS Area5PASCAL VOC 2012 testS3DISScanNetSUN-RGBDDensePASS

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1InternImage-H (M3I Pre-training)Params (M)1,310—Unverified
2ViT-P (InternImage-H)Validation mIoU63.6—Unverified
3ONE-PEACEValidation mIoU63—Unverified
4M3I Pre-training (InternImage-H)Validation mIoU62.9—Unverified
5InternImage-HValidation mIoU62.9—Unverified
6BEiT-3Validation mIoU62.8—Unverified
7EVAValidation mIoU62.3—Unverified
8ViT-P (OneFormer, InternImage-H)Validation mIoU61.6—Unverified
9ViT-Adapter-L (Mask2Former, BEiTv2 pretrain)Validation mIoU61.5—Unverified
10FD-SwinV2-GValidation mIoU61.4—Unverified